Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
| Parental Level,Game Title,File Offset,PlayStation PRO Support,Current Version,Instant Download,Package Size,PlayStation VR,Piece,SHA1 Hash,Title ID,Play Together | |
| 3,THE PLAYROOM,0,No,1.07,http://gs2.ww.prod.dl.playstation.net/gs2/ppkgo/prod/CUSA00001_00/9/f_ef965b581d35637dabc96366f29f1f0ece58c8fa9158b0eb7de9407ae72272e8/f/IP9100-CUSA00001_00-PLAYROOM00000000-A0107-V0100.pkg,34.9MB,No,0,22774b6c655f47dffce0eb7e15c5e865dce6a849,CUSA00001_00, | |
| 9,KILLZONE SHADOW FALL,0,No,1.81,http://gs2.ww.prod.dl.playstation.net/gs2/ppkgo/prod/CUSA00002_00/58/f_0882efa770fbf5b9a03b4decce248e8f07fd9585cbe43c44791799952c62fd14/f/EP9000-CUSA00002_00-KZ4RELEASE000041-A0181-V0100.pkg,2.9GB,No,0,552b7127dac3ee8ab5ce2ae051f6436c3ec605fc,CUSA00002_00, | |
| 7,inFAMOUS Second Son,0,Yes,1.07,http://gs2.ww.prod.dl.playstation.net/gs2/ppkgo/prod/CUSA00004_00/28/f_2881c3732328a643917aeb4c1e73b916c1d6baa7ea09e2e81f33d5f139ea9449/f/EP9000-CUSA00004_00-SECONDSONSHIP000-A0107-V0100.pkg,3.7GB,No,0,0538bdff843286013877ab92e5dc936b1407ddcb,CUSA00004_00, |
8B F1 E8 40 CD 05 00 8B 7D 10 83 F8 02 0F 94 C3.31 C0 E9 2D 01 00 00 90 90 90 90 90 90 90 90 90.engine.dll.Reference: patching sub_1013BF40 result to successfully return always fixes the constant "No Steam logon\n" error. Meant for Portal Reloaded.
Python usage: python3 patch.py engine.dll
| // ==UserScript== | |
| // @name Draft W3C Process Document modularization menu | |
| // @description This adds a menu to modularize the Editor's Draft of the W3C Process Document as discussed in https://github.com/w3c/process/issues/1188 | |
| // @namespace https://tidoust.net/ | |
| // @version 1.0.1 | |
| // @match https://www.w3.org/policies/process/drafts/* | |
| // @grant none | |
| // ==/UserScript== |
| echo "🧹 Resetting CrossOver bottles..." | |
| pkill CrossOver && echo "✅ CrossOver processes killed." | |
| echo "🕒 Modifying trial timestamps..." | |
| DATETIME=$(date -u -v -3H '+%Y-%m-%dT%TZ') | |
| echo "✅ New trial date set to: ${DATETIME}" | |
| defaults write com.codeweavers.CrossOver FirstRunDate -date "${DATETIME}" | |
| defaults write com.codeweavers.CrossOver SULastCheckTime -date "${DATETIME}" | |
| echo "✅ Updated trial timestamps in preferences." | |
| echo "🧹 Resetting CrossOver bottles..." | |
| find ~/Library/Application\ Support/CrossOver/Bottles/ -type f \( -name ".eval" -o -name ".update-timestamp" \) -exec rm -f "{}" + |
.env file for me sparing me the need to pollute my session with environment variables.
I've been using Fish shell for years which is great and all, but one thing that has got me frustrated is using it with .env files.
When attempting to run source .env in a project, I usually encounter this problem:
Download the Installer: Visit the GitHub repository provided in the link: https://github.com/garyan2/wmcsetup/releases/latest/download/wmcsetup-x64.msi and download the installer file wmcsetup-x64.msi to your computer.
Run the Installer: Once the download is complete, locate the downloaded file (wmcsetup-x64.msi) on your computer and double-click it to run the installer.
Install Windows Media Center: Follow the on-screen instructions provided by the installer to install Windows Media Center on your system. You may need to accept license agreements and choose installation options during this process. Make sure to review the options carefully before proceeding.
Complete the Installation:
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| // Copyright (c) October 2026 Félix-Olivier Dumas. All rights reserved. | |
| // Licensed under the terms described in the LICENSE file | |
| #include <iostream> | |
| #include <immintrin.h> | |
| int main() { | |
| float a[8] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; | |
| float b[8] = { 10.0f, 20.0f, 30.0f, 40.0f, 50.0f, 60.0f, 70.0f, 80.0f }; |